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INTRODUCTION: In order to prevent and reduce the death and disability rates caused by road accidents, it is necessary to optimize the location of the roadside emergency medical service (EMS) stations. Optimal selection of the EMS stations is a multi-criteria decision-making (MCDM) problem and usually involves the analysis of a large number of possible options and evaluation criteria. Nowadays, various MCDM methods are used to solve location problems that may generate different results. The fuzzification of these methods has always been one of the controversial issues with many agreements and disagreements. METHODS: In this study, a review was first performed on the weighting methods including five non-fuzzy weighting methods as row sum, column sum, arithmetic mean, geometric mean, and eigenvalues as well as two fuzzy weighting methods including: “Liu and Chen method” and “Chang Method”. Then, the fuzzy and non-fuzzy MCDM methods [including analytic hierarchy process (AHP), fuzzy analytic hierarchy process (FAHP) Chang, FAHP Liu, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and fuzzy TOPSIS (FTOPSIS)] were employed to locate the roadside EMS stations. Due to insufficient information and all the required layers in Iran, the information of the Interstate-65 (I-65) Highway between Montgomery and Birmingham, Alabama, USA was used in the present study. Finally, the results of these methods were compared using the mean-score, Borda, and Copeland prioritization strategies. FINDINGS: Given the importance and sensitivity of the issue, a combination of the MCDM methods was utilized to locate the EMS stations and the most appropriate non-fuzzy and fuzzy weighting methods were identified and the methods used were compared in terms of complexity, volume and time of computations, and the level of impact of the expert opinion. CONCLUSION: The AHP, FAHP Liu and Chen, FAHP Chang, and TOPSIS methods yielded more reliable results in locating the roadside EMS stations, in addition, using FTOPSIS fuzzy method was more risky and is not recommended. The non-fuzzy AHP method was identified to be the most reliable method in the present study.
